Internal Medicine

"Knowledge from systematically analyzing missed opportunities in correct or timely diagnosis will inform improvements and create a learning health system for diagnosis," Dr. Singh says. The network, known as Pride, short for Primary Care Research in Diagnostic Errors, plans to identify, analyze and classify diagnostic errors and delays with the help of electronic medical records, to develop and share interventions that can overcome diagnostic errors and delays, especially in primary care. It also plans to help doctors avoid ordering unnecessary and wasteful tests by developing "principles of conservative diagnosis," says Gordon Schiff, associate director of Brigham and Women's division of general internal medicine and quality and safety director at Harvard Medical School's Center for Primary Care. In response, the project plans to develop and test "loop-closing" tools for electronically tracking doctors' recommendations of tests and procedures that aren't carried out.

Stanford's review board approved Kosinski and Wang's study. "The vast, vast, vast majority of what we call'big data' research does not fall under the purview of federal regulations," says Metcalf. Take a recent example: Last month, researchers affiliated with Stony Brook University and several major internet companies released a free app, a machine learning algorithm that guesses ethnicity and nationality from a name to about 80 percent accuracy. The group also went through an ethics review at the company that provided training list of names, although Metcalf says that an evaluation at a private company is the "weakest level of review that they could do."

Stanford's review board approved Kosinski and Wang's study. "The vast, vast, vast majority of what we call'big data' research does not fall under the purview of federal regulations," says Metcalf. Take a recent example: Last month, researchers affiliated with Stony Brook University and several major internet companies released a free app, a machine learning algorithm that guesses ethnicity and nationality from a name to about 80 percent accuracy. The group also went through an ethics review at the company that provided training list of names, although Metcalf says that an evaluation at a private company is the "weakest level of review that they could do."

Zipline, a pioneering drone startup that began delivering blood packs to Rwanda's remote hospitals in October 2016, today announced a major expansion into Tanzania. In early 2018 the company will begin flying its delivery drones to more than 1000 health care facilities around Tanzania, bringing urgently needed medicines and supplies to big hospitals and tiny rural clinics alike. He ticks off the hard parts of operating an automated, drone-delivery system at national scale: making sure all regulatory issues are resolved; finding and training a local team to operate the distribution centers; spreading word to doctors and health care workers about the service; and communicating with people in towns and villages who see the drones whizzing overhead. In Rwanda, Zipline has flown 1,400 delivery flights since service began in October 2016.

Desperate, the doctors called a distribution center near Kigali, where clinic workers and a flight crew loaded a series of small, unmanned aircraft with the needed supplies and launched them into the sky. The Tanzanian government wants to make as many as 2,000 daily deliveries from four distribution centers serving an area roughly the size of Texas and Louisiana. Each can carry 3 pounds of cargo (one unit of blood weighs roughly 1.2 pounds), and the batteries can make a round trip of 100 miles. Zipline makes a habit of recruiting and training local engineers, health workers, and flight operators.

Picture this: a patient walks into the emergency department and sits in front of the "triage nurse" -- a computer that uses advanced algorithms to ask questions based on the patient's answers. Researchers at the Massachusetts Institute of Technology (MIT) are testing robotic decision supports that schedule nursing tasks and assign rooms to patients. TAVIE uses pre-recorded videos of a nurse to coach patients to manage their health condition and make behaviour changes. Ryan Chan, an emergency nurse and a master's student, is working with Booth and his research team as they develop an online computer game to teach electronic medication administration to nursing students.

But the AI's work isn't done yet. Comparing the change in genetic code with infection rates and virulence factors could give us a better model for working toward a vaccine for this insufferable virus. And if we finally managed to program an AI that would tell us how it arrives at its conclusions, that would be a powerful collaboration indeed. Imagine an AI that evolves with the virus it tracks.

The Center on Artificial Intelligence for Social Solutions (CAISS) has developed a tool which identifies peer leaders within Los Angeles' homeless community to spread awareness about HIV prevention. The chatbots use natural language processing on Facebook Messenger. In addition, the CC-Cruiser will be able to utilize big data by pooling worldwide cases to improve the AI further. Inbenta is a leader in natural language processing and artificial intelligence for customer support, e-commerce and conversational chatbots, providing an easy-to-deploy solution that improves customer satisfaction, reduces support costs, and increases revenue.

And, wait, are internists doctors who specialize in internal medicine - or just their interns? But the complexities of medical jargon can make an already complicated U.S. health system even more convoluted for millions of people seeking care. Click here to subscribe to Brainstorm Health Daily, our brand new newsletter about health innovations. This essay appears in today's edition of the Fortune Brainstorm Health Daily.

Intermountain Healthcare has approximately 150 protocols built into its electronic health record (EHR) system, alerting clinicians when the patient information they enter indicates certain conditions and then guiding them through further examinations and potential treatments. A 12-member team of doctors, nurses and analytics experts takes upwards of a year to analyze data and build each protocol, said Marc Probst, the chief information officer at the not-for-profit health system based in Salt Lake City. We're going to be in the thousands of protocols soon," Probst said, adding that Intermountain is now piloting AI use in building protocols. "In many ways, this is just a natural evolution of an ecosystem," said Anil Jain, MD, FACP, vice president and chief health informatics officer with IBM Watson Health, a staff physician in internal medicine at Cleveland Clinic, and a long-standing member and contributor with the nonprofit American Medical Informatics Association (AMIA), which promotes the development and application of biomedical and health informatics in patient care.